- 标题
- 摘要
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- 实验方案
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[IEEE 2018 IEEE Western New York Image and Signal Processing Workshop (WNYISPW) - Rochester, NY, USA (2018.10.5-2018.10.5)] 2018 IEEE Western New York Image and Signal Processing Workshop (WNYISPW) - INCREMENTAL COMPLEX L1-PCA FOR DIRECTION-OF-ARRIVAL ESTIMATION
摘要： In wireless-node localization, the receiver processes snapshots collected by its antenna array in order to estimate the direction-of-arrival (DoA) of a source of interest. High-resolution direction finding is commonly carried out by principal-component analysis (PCA) of the collected complex-valued snapshots (subspace-based methods). Standard PCA was recently replaced by corruption-resistant L1-PCA in order to counteract the detrimental impact of unexpected, intermittent jamming. In this paper, we present the first incremental method for complex L1-PCA and employ it for online direction finding, as snapshots naturally arrive in a streaming fashion. Our numerical studies corroborate the computational efficiency and jamming/corruption resistance of the proposed method.
关键词： SVD,Array processing,corrupted data,L1-norm,L1-PCA,direction finding
更新于2025-09-23 15:22:29
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A Skeleton-Based Hierarchical Method for Detecting 3-D Pole-Like Objects From Mobile LiDAR Point Clouds
摘要： The pole-like object detection is of signi?cance for robot navigation, autonomous driving, road infrastructure inventory, and detailed 3-D map generation. In this letter, we develop a skeleton-based hierarchical method for automatic detection of pole-like objects from mobile LiDAR point clouds. First, coarse extraction of building facades is adopted for the occlusion analysis. Second, slice-based Euclidean clustering algorithm is implemented to derive a set of pole-like object candidates. Third, skeleton-based principal component analysis shape recognition is presented to robustly locate all possible positions of pole-like objects. Finally, a Voronoi-constrained vertical region growing algorithm is proposed to adaptively producing the individual pole-like objects. Experiments were conducted on the public Paris–Lille-3-D data set. Experimental results demonstrate that the proposed method is robust and ef?cient for extracting the pole-like objects, with average quality of 90.43%. Furthermore, the proposed method outperforms other existing methods, especially for detecting pole-like objects with a large radius.
关键词： pole-like object extraction,Voronoi tessellation,Laplacian smoothing,principal component analysis (PCA)
更新于2025-09-23 15:22:29
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - A Multi-Direction Subbands and Deep Neural Networks Bassed Pan-Sharpening Method
摘要： This paper proposes a pan-sharpening method based on multi-direction subbands and deep neural networks. First, by utilizing the multi-scale and multi-direction properties of the nonsubsampled contourlet transform (NSCT), panchromatic (PAN) image is decomposed into the low frequency subbands in different resolutions and the high frequency subbands in different directions. Pan-sharpening method aims to fuse the high frequency subband coefficients of PAN image and the low frequency subband coefficients of multispectral (MS) image. Second, in order to better extract the feature of the high frequency subbands in different directions of PAN image, the deep neural network (DNN) is trained using the image patches of high frequency subbands of PAN image. Third, in the fusion stage, we exploit NSCT on the principal component of resampled low resolution (LR) MS image. The high frequency subbands of output high resolution (HR) MS image is obtained by forward propagation of the trained DNN, which input is the high frequency subbands of LR MS image. Finally, a new subband set is obtained by fusing the reconstructed high frequency subband and the original low frequency subband of LR MS image. The HR MS image is produced by executing the inverse transform of NSCT and adaptive PCA (A-PCA) on the new subband set. The experimental results show the proposed method outperforms other well-known methods in terms of both objective measurements and visual evaluation.
关键词： adaptive Principal Component Analysis (A-PCA),deep neural network (DNN),pan-sharpening,nonsubsampled contourlet transform (NSCT)
更新于2025-09-23 15:22:29
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Comparison of Different Types of Near Infrared (NIR) Instruments in Ability to Measure Alkaloids in Capsule of Poppy (P. somniferum)
摘要： The poppy capsule is one of the most important raw materials for the pharmaceuticals industry containing in about 25 different alkaloids. Among these there are important substances, such as morphine, with analgesic and anaesthetic properties, anti-tussive codeine, and noscapine with anti-tumor activity. My first objective was comparing dispersive and Fourier transformed (FT) near-infrared (NIR) instruments in order to measure alkaloids using the same sample population via mathematical pre-treatments (i.e. gap-segment derivatives) of the spectra and partial least squares (PLS) calibrations. The best PLS calibration using cross validation (CV) was for morphine based on derivative spectra of dispersive NIR with R-square (R2) 0.924 and root mean square error (RMSE) 1.198 mg (g dry matter)–1 in 1.24–20.44 mg (g dry matter)–1 range. Comparison of the changes in the output of the PLS parameter for the two instruments revealed a variance depending on the derivative and the segment size.
关键词： NIR,alkaloids,poppy capsule,PCA
更新于2025-09-23 15:22:29
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Improving Diagnosis of Cervical Pre-Cancer: Combination of PCA and SVM Applied on Fluorescence Lifetime Images
摘要： We report a signi?cant improvement in the diagnosis of cervical cancer through a combined application of principal component analysis (PCA) and support vector machine (SVM) on the average ?uorescence decay pro?le of Fluorescence Lifetime Images (FLI) of epithelial hyperplasia (EH) and CIN-I cervical tissue samples, obtained ex-vivo. The fast and slow components of double exponential ?tted ?uorescence lifetimes were found to be higher for EH compared to the lifetimes of CIN-I samples. Application of PCA to the average time-resolved ?uorescence decay pro?les showed that the 2nd PC, in combination with 1st PC, enhanced the discrimination between EH and CIN-I tissues. Fluorescence lifetime and PC scores were then classi?ed separately by using SVM support vector machine to identify the two. On applying SVM to a combination of ?uorescence lifetime and PC scores, diagnostic capability improved signi?cantly.
关键词： PCA,?uorescence lifetime,SVM,PC scores
更新于2025-09-23 15:22:29
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[IEEE 2018 IEEE International Conference on Imaging Systems and Techniques (IST) - Krakow, Poland (2018.10.16-2018.10.18)] 2018 IEEE International Conference on Imaging Systems and Techniques (IST) - 2D Multi-Band PCA and its Application for Ear Recognition
摘要： Principal Component Analysis (PCA) has been successfully used for many application including ear recognition. However, its performance is limited due to its significant data dependency. This paper presents a two dimensional multi-band PCA (2D-MBPCA) method, which has shown a significantly higher performance to that of the PCA. The proposed method divided the input gray image into a number of images, based on the intensity of its pixels using either a dynamic or predefined equal range of threshold values. PCA is then applied on the resulting set of images to extract their features. The resulting features are used to find the best match. The application of the proposed 2D-MBPCA for ear recognition using two benchmark ear image datasets, shows the merit of the proposed technique to that of the standard PCA.
关键词： ear recognition,histogram equalization,PCA
更新于2025-09-23 15:22:29
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[IEEE NAECON 2019 - IEEE National Aerospace and Electronics Conference - Dayton, OH, USA (2019.7.15-2019.7.19)] 2019 IEEE National Aerospace and Electronics Conference (NAECON) - In Situ Process Monitoring for Laser-Powder Bed Fusion using Convolutional Neural Networks and Infrared Tomography
摘要： Additive Manufacturing (AM) is a growing field for various industries of avionics, biomedical, automotive and manufacturing. The onset of Laser Powder Bed Fusion (LPBF) technologies for metal printing has shown exceptional growth in the past 15 years. Quality of parts for LPBF is a concern for the industry, as many parts produced are high risk, such as biomedical implants. To address these needs, a LPBF machine was designed with in-situ sensors to monitor the build process. Image processing and machine learning algorithms provide an efficient means to take bulk data and assess part quality, validating specific internal geometries and build defects. This research will analyze infrared (IR) images from a Selective Laser Melting (SLM) machine using a Computer Aided Design (CAD) designed part, featuring specific geometries (squares, circles, and triangles) of varying sizes (0.75-3.5 mm) on multiple layers for feature detection. Applying image processing to denoise, then Principal Component Analysis (PCA) for further denoising and applying Convolution Neural Networks (CNN) to identify the features and identifying a class which does not belong to a dataset, where a dataset are created from CAD images. Through this automated process, 300 geometric elements detected, classified, and validated against the build file through CNN. In addition, several build anomalies were detected and saved for end-user inspection.
关键词： Laser Powder Bed Fusion (LPBF),Principal Component Analysis (PCA),infrared image (IR),Convolution Neural Networks (CNN),Additive Manufacturing (AM),Computer Aided Design (CAD)
更新于2025-09-23 15:21:01
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[IEEE 2019 IEEE Conference on Power Electronics and Renewable Energy (CPERE) - Aswan City, Egypt (2019.10.23-2019.10.25)] 2019 IEEE Conference on Power Electronics and Renewable Energy (CPERE) - Common-Mode Voltage Analysis of Three-phase Quasi-Z Source Inverters for Transformerless Photovoltaic Systems
摘要： Reducing the capacitance of programmable capacitor arrays (PCAs), commonly used in analog integrated circuits, is necessary for low-energy applications. However, limited mismatch data are available for small capacitors. We report mismatch measurement for a 2-fF poly–insulator–poly (PIP) capacitor, which is the smallest reported PIP capacitor to the best of the authors’ knowledge. Instead of using complicated custom on-chip circuitry, direct mismatch measurement is demonstrated and veri?ed using Monte Carlo simulations and experimental measurements. Capacitive test structures composed of 9-bit PCAs are implemented in a low-cost 0.35-μm CMOS process. Measured data are compared to the mismatch of large PIP capacitors, theoretical models, and recently published data. Measurement results indicate an estimated average relative standard deviation of 0.43% for the 2-fF unit capacitor, which is better than the reported mismatch of metal–oxide–metal (MOM) fringing capacitors implemented in an advanced 32-nm CMOS process.
关键词： programmable capacitor array (PCA),Analog-to-digital converter (ADC),energy-ef?cient circuits,mismatch characterization,capacitance-to-digital converter (CDC),capacitor mismatch
更新于2025-09-23 15:21:01
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Rapid qualitative evaluation of velvet antler using laser-induced breakdown spectroscopy (LIBS)
摘要： The aim of this work is to study a rapid analysis method to evaluate velvet antler products qualitatively, using laser-induced breakdown spectroscopy (LIBS). We used principal component analysis to select feature lines of LIBS spectra of velvet antler, and built two partial least squares-discriminant analysis (PLS-DA) classification models to distinguish between inferior and good quality velvet antler by using the intensities of all lines and feature lines as input variables, respectively. The correct classification rates (CCRs) of these two models were both 100%. In order to test the robustness of the models, we used these two models to discriminate the samples not included in the training set to build the model, and the CCRs were 87.5% and 100%, respectively. The results demonstrated that combining LIBS with PLS-DA could evaluate the quality of velvet antler, and the robustness could be improved by using the intensities of feature lines as inputs.
关键词： qualitative evaluation,partial least squares-discriminant analysis (PLS-DA),velvet antler,principal component analysis (PCA),laser-induced breakdown spectroscopy (LIBS)
更新于2025-09-23 15:19:57
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[IEEE 2019 IEEE 2nd International Conference on Renewable Energy and Power Engineering (REPE) - Toronto, ON, Canada (2019.11.2-2019.11.4)] 2019 IEEE 2nd International Conference on Renewable Energy and Power Engineering (REPE) - The Potential and analysis of Grid-connected Photovoltaic System in residential houses in Libya : Near-term solution of electricity shortage: A case study in Tripoli
摘要： Reducing the capacitance of programmable capacitor arrays (PCAs), commonly used in analog integrated circuits, is necessary for low-energy applications. However, limited mismatch data are available for small capacitors. We report mismatch measurement for a 2-fF poly–insulator–poly (PIP) capacitor, which is the smallest reported PIP capacitor to the best of the authors’ knowledge. Instead of using complicated custom on-chip circuitry, direct mismatch measurement is demonstrated and veri?ed using Monte Carlo simulations and experimental measurements. Capacitive test structures composed of 9-bit PCAs are implemented in a low-cost 0.35-μm CMOS process. Measured data are compared to the mismatch of large PIP capacitors, theoretical models, and recently published data. Measurement results indicate an estimated average relative standard deviation of 0.43% for the 2-fF unit capacitor, which is better than the reported mismatch of metal–oxide–metal (MOM) fringing capacitors implemented in an advanced 32-nm CMOS process.
关键词： programmable capacitor array (PCA),Analog-to-digital converter (ADC),energy-ef?cient circuits,mismatch characterization,capacitance-to-digital converter (CDC),capacitor mismatch
更新于2025-09-23 15:19:57